Impact sensors can be installed on vehicles to monitor impacts the vehicle encounters. Most impact sensors are adapted to set an impact threshold level based on environmental conditions in which the vehicle is most likely to operate. For example, the threshold level for a vehicle that generally operates on a smooth, asphalt-like surface is most likely lower than a threshold level for a vehicle that generally operates on a rough, gravel-like terrain. If the vehicle encounters an impact that exceeds the threshold level, the sensor may then record the impact. This recorded impact can subsequently be analyzed to study the driving habits of a particular vehicle or a particular driver.
Many impact sensors of the prior art require custom tuning of thresholds. Custom tuning of thresholds generally requires exposing the vehicle to a “learning mode” test, wherein data is collected and analyzed. A repeated analysis of the data is often required to set an accurate threshold. This analysis can be done manually, which is expensive and complex, or automatically. Once tuned, the threshold is kept static, regardless of changing environmental conditions, unless a person manually initiates a new learning mode. Therefore, impact sensors installed on vehicles that travel from smooth, asphalt-like terrain to rough, gravel-like terrain create false positive and false negative impact events.
Accordingly, there is a need for an impact sensor that adapts to varying terrain conditions and can be automatically configured without human intervention or any need to collect pre-data, wirelessly or otherwise. There is also a need for an impact sensor that can distinguish between varieties of severity levels. It is to these needs that the present invention is directed.